### Abstract

Lingua originale | English |
---|---|

Stato di pubblicazione | Published - 2014 |

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### All Science Journal Classification (ASJC) codes

- Energy Engineering and Power Technology
- Fuel Technology

### Cita questo

*Mixed heuristic-non linear optimization of energy management for hydrogen storage-based multi carrier hubs*.

**Mixed heuristic-non linear optimization of energy management for hydrogen storage-based multi carrier hubs.** / Miceli, Rosario; Zizzo, Gaetano; Riva Sanseverino, Eleonora; La Cascia, Diego; Bertoncini, Massimo; Arnone, Diego; Proietto, Rosario; Rossi, Alessandro.

Risultato della ricerca: Paper

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TY - CONF

T1 - Mixed heuristic-non linear optimization of energy management for hydrogen storage-based multi carrier hubs

AU - Miceli, Rosario

AU - Zizzo, Gaetano

AU - Riva Sanseverino, Eleonora

AU - La Cascia, Diego

AU - Bertoncini, Massimo

AU - Arnone, Diego

AU - Proietto, Rosario

AU - Rossi, Alessandro

PY - 2014

Y1 - 2014

N2 - In this paper, an heuristic and non-linear programming based algorithm to optimally operate an energy hub plant is proposed. The energy hub plant described in this work is the test system for the European INGRID research project. The Energy Management System defines the optimal energy flows dispatch in order to obtain the energy balance and the maximum profit for the owner of the plant. The problem is highly constrained and non-linear, for this reason the methodology cannot rely on Linear Programming (LP) methods. The Energy Management System manages two energy carriers, electricity and hydrogen, interfacing three distribution networks: the electricity, the hydrogen and the methane networks. Simulations show that the buffer function of the system is as more intense as greater the efficiency of the conversion systems is, as compared to the prices variations along the day. Although heuristic search methods are well-suited for the solution of highly constrained non-linear problems, the applications carried out over the INGRID project test-bed show that improved solutions can be found applying a non-linear programming method named Generalised Reduced Gradient (GRG), to refine the solutions outputted by heuristic algorithms, such as Simulated Annealing or Tabu Search.

AB - In this paper, an heuristic and non-linear programming based algorithm to optimally operate an energy hub plant is proposed. The energy hub plant described in this work is the test system for the European INGRID research project. The Energy Management System defines the optimal energy flows dispatch in order to obtain the energy balance and the maximum profit for the owner of the plant. The problem is highly constrained and non-linear, for this reason the methodology cannot rely on Linear Programming (LP) methods. The Energy Management System manages two energy carriers, electricity and hydrogen, interfacing three distribution networks: the electricity, the hydrogen and the methane networks. Simulations show that the buffer function of the system is as more intense as greater the efficiency of the conversion systems is, as compared to the prices variations along the day. Although heuristic search methods are well-suited for the solution of highly constrained non-linear problems, the applications carried out over the INGRID project test-bed show that improved solutions can be found applying a non-linear programming method named Generalised Reduced Gradient (GRG), to refine the solutions outputted by heuristic algorithms, such as Simulated Annealing or Tabu Search.

UR - http://hdl.handle.net/10447/97993

M3 - Paper

ER -